Title of Talk: A genomic approach for designing the next generation of coal-based technological materials

Disordered carbon materials, both amorphous and with long-range order (such as reduced graphene oxide), have been used in a variety of applications, from conductive additives and contact materials to transistors and photovoltaics, to nano-filtering and separation membranes. Yet, despite some apparent similarities, natural carbonaceous materials (such as coal, pitch and tar) have not been extensively used as is or as derived feedstock to produce advanced technological materials. In this talk, I will discuss how a genomic inspired approach in modeling coal can be used for guiding application driven design of coal-based materials. Rather than customizing a top-down coal model to specific material needs, we start by “sequencing” or fingerprinting relevant molecular fragments to construct sample-specific models. Using molecular dynamics and density functional theory, we prioritize the molecular and chemical structures and functionals responsible for a particular global property (electrical and thermal conductivity, hardness, stiffness, etc.) as well to define experimental parameters in a manufacturing process. As an example of such computationally driven, experimentally optimized approach, we will discuss the design of coal-based electronic thin films. Processed optimized coal-based thin-films exhibit the electrical conductivity in excess of 7 orders of magnitude, encompassing the variability normally obtained through several carbon based synthetic nanomaterials within just one starting coal. By improving the material selection and film morphology state-of the-art natural carbon-based transparent joule resistors are fabricated with fine control over their conductivity. Finally, I will conclude with an outline of how this genomic approach to coal will be essential in the next generation of coal-based nanofiltration membranes, currently based on reduced graphene-oxide.